M Hallett
January 2015
www.bci.mcgill.ca My lab website
www.bci.mcgill.ca/home/?page_id=811 Course Website
TRF 10:35am-11:25am
ENGTR – Trottier Building 2110
Jan 5th 2015 – April 14th 2015
\( {\tt michael.t.hallett@mcgill.ca} \)
Office: Bellini 434
Office Hours: TBA
Daniel Del Balso, Teaching Assistant
\( {\tt daniel.delbalso2@mail.mcgill.ca} \)
Office: Bellini 432
Office Hours: TBA
| Exercise | Due Date | % of Grade |
|---|---|---|
| Assignment 0 | Friday, January 16th, 2015 | 10% |
| Assignment 1 | Tuesday February 3rd, 2015) | 10% |
| Assignment 2 | Tuesday, February 17th, 2015 | 10% |
| Midterm | February 27th, 2015 | 20% |
| Assignment 3 | March 10th, 2015 | 10% |
| Assignment 4 | March 24th, 2015 | 10% |
| Final Exam | TBA | 30% |
So Pubmed allowed researchers to identify papers that mentioned a gene (eg ESR).
(A lot of Principle Investigators (PIs) still primarily and only use PubMed to track their genes.)
But what about results related to ESR that are derived from -omic/systems biology efforts.
Eg. every time an individual is sequenced, their ESR gene is sequenced and any mutations in this gene add to the global pool of polymorphisms?
Eg. every time a higher-order eukaroyte is sequenced, a homologue of ESR is sequenced (and may not be named ESR)?
Eg. every time a gene expression microarray is performed on a human sample, ESR levels are of course measured, since these microarrays cover the complete transcriptome?
Eg. every time a mass spectrometry experiment is performed to identify proteins or protein interactions, ESR will have be measured too?
GenBank '88, dbGap '07 and many other databases provide all of this information.
Can researchers afford to ignore this information and only look at the primary research?
Bioinformatic software was necessary to perform complicated, statistical searches that allow researchers to track their genes in these datasets.
Managing biological information is a part of bioinformatics but not all
Bioinformatics is also the investigation of biological systems using tools from information science.
Often this is about hypothesis testing and biomarker discovery.
For example, the development of gene panels like Oncotype DX www.oncotypedx.com
For example, my lab considers itself to be a breast cancer research lab whose primary assay is bioinformatics (as opposed to pull downs, PCR, microarray or other assays).
For example, models of the genome, exome, transcriptome, proteome, protein interactome, methylomes, epigenome, … and many other -omic entities.
Hypothesis testing, biomarkers, and model building all require a tremendous amount of tools from biostatistics and computation.
The HapMap project that catalogs single nucleotide polymorphisms and other mutations in human populations.
Gene Expression Omnibus and other efforts seek to catalogue transcriptional (mRNA expression levels)
The Epigenome project that is attempting to catalogue all epigenetic modifications (e.g. methylation) in different types of human cells (e.g neuronal versus epithelial vs fibroblasts vs endothelial etc.).
Networks that capture which pairs of proteins interact within a cell or organism. Here this is a bacteria (Treponema palladium). Nodes are proteins and edges (lines) connect two proteins that have been determined to interact. Interactions can be between proteins within a complex (e.g. proteins that comprise the ribosome), proteins that phosphorylate other proteins within signalling cascasdes, protein chaperones that help other proteins fold, or …
Historically,biological models are simple and deterministic
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